TY - JOUR
T1 - Cuproptosis in ccRCC
T2 - key player in therapeutic and prognostic targets
AU - Lv, Yang
AU - Li, Qiang
AU - Yin, Lu
AU - He, Shaohua
AU - Qin, Chao
AU - Lu, Zhongwen
AU - Chen, Hongqi
N1 - The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The Mechanism and Clinical Application of Nrf3 Methylated m6A Modification in Environmental Endocrine Disruptor-Induced Male Erectile Dysfunction (Suzhou Science and Technology Plan Project No.: SKJYD2021030). CircRNALPAR3’s Clinical Diagnosis and Treatment Judgment and Related Mechanisms of Prostate Cancer (Suzhou Science and Technology Plan Project No.: SKY2022032). LncRNA-AC124854.1 participates in the reactivation of PI3K/ AKTmTOR pathway by regulating the expression of microtubule- associated protein 4 and promotes the clinical application of drug resistance in kidney cancer BEZ235 (Project No.: wwk202104). “Effects of the Chinese medicine Cat's Whiskers on Chronic Renal Failure” (Project number of "Promoting Health through Science and Education" in Wujiang District, Suzhou City: wwk201717). Research on the Application of Transrectal Ultrasound Targeted Injection of Silk Fibroin/Iron Oxide Composite Hydrogel Magnetic Heat in the Treatment of Prostate Cancer" (Suzhou Science and Technology Plan Project Number: SKYD2023023).
Publisher Copyright:
Copyright © 2023 Lv, Li, Yin, He, Qin, Lu and Chen.
PY - 2023/10/27
Y1 - 2023/10/27
N2 - Background: Classical biomarkers have been used to classify clear cell renal cell carcinoma (ccRCC) patients in a variety of ways, and emerging evidences have indicated that cuproptosis is closely related to mitochondrial metabolism, thereby accelerating the development and progression of ccRCC. Nevertheless, the specific relationship between cuproptosis and the prognosis and treatment of ccRCC remains unclear. Methods: We comprehensively integrated several ccRCC patient datasets into a large cohort. Following that, we systematically analyzed multi-omics data to demonstrate the differences between two cuproptosis clusters. Results: We identified two cuproptosis clusters in ccRCC patients. Among the two clusters, cluster 1 patients showed favorable prognosis. We then confirmed the significant differences between the two clusters, including more typical cancer hallmarks were enriched in cluster 2 patients; cluster 2 patients were more susceptible to develop mutations and had a lower level of gistic score and mRNAsi. Importantly, both Tumor Immune Dysfunction and Exclusion analysis and subclass mapping algorithm showed that cuproptosis 1 patients were more susceptible to be responded to immunotherapy. In addition, a prognostic signature was successfully developed and also showed prominent predictive power in response to immunotherapy.Conclusion: As a result of our findings, we were able to classify ccRCC patients according to cuproptosis in a novel way. By constructing the cuproptosis clusters and developing the signature, patients with ccRCC could have a more accurate prognosis prediction and better immunotherapy options.
AB - Background: Classical biomarkers have been used to classify clear cell renal cell carcinoma (ccRCC) patients in a variety of ways, and emerging evidences have indicated that cuproptosis is closely related to mitochondrial metabolism, thereby accelerating the development and progression of ccRCC. Nevertheless, the specific relationship between cuproptosis and the prognosis and treatment of ccRCC remains unclear. Methods: We comprehensively integrated several ccRCC patient datasets into a large cohort. Following that, we systematically analyzed multi-omics data to demonstrate the differences between two cuproptosis clusters. Results: We identified two cuproptosis clusters in ccRCC patients. Among the two clusters, cluster 1 patients showed favorable prognosis. We then confirmed the significant differences between the two clusters, including more typical cancer hallmarks were enriched in cluster 2 patients; cluster 2 patients were more susceptible to develop mutations and had a lower level of gistic score and mRNAsi. Importantly, both Tumor Immune Dysfunction and Exclusion analysis and subclass mapping algorithm showed that cuproptosis 1 patients were more susceptible to be responded to immunotherapy. In addition, a prognostic signature was successfully developed and also showed prominent predictive power in response to immunotherapy.Conclusion: As a result of our findings, we were able to classify ccRCC patients according to cuproptosis in a novel way. By constructing the cuproptosis clusters and developing the signature, patients with ccRCC could have a more accurate prognosis prediction and better immunotherapy options.
KW - clear cell renal cell carcinoma
KW - cuproptosis
KW - immunotherapy
KW - prognosis
KW - tumor immune microenvironment
UR - http://www.scopus.com/inward/record.url?scp=85176575984&partnerID=8YFLogxK
UR - https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1271864/full
U2 - 10.3389/fonc.2023.1271864
DO - 10.3389/fonc.2023.1271864
M3 - Journal article
AN - SCOPUS:85176575984
SN - 2234-943X
VL - 13
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 1271864
ER -